Retail and CPG Analytics
Retailers and CPG companies achieve breakthrough business outcomes by leveraging analytics automation on internal and external data to develop actionable insight into the needs of customers across products, channels, and other factors that influence demand.
Stay Relevant
On shelf availability and out of stock conditions remain among the most significant challenges facing retailers and their CPG partners. Meanwhile, shopping trends change rapidly, exposing retailers to lost sales when assortment falls out of favor, placing pressure on trade relationships that rely on promotions at the expense of margin. Shipping and fulfillment costs for e-commerce and other channels strain margins further and are a barrier for many emerging direct to consumer CPG programs as well.
These are Analytics Automation problems requiring access to a variety of internal and external data indicative of the ever-changing preferences of customers.
- Gain a clear line of sight into the consumption behaviors of customers
- Drop poor performing SKUs while filling relevant gaps with high demand products
- Access all useful demand signals to co-create value-based trade promotion
- Align marketing investments with dynamic consumer behavior
- Optimize inbound, outbound, and reverse logistics
Automating the Analytics Process
Data Preparation and Blending
Automate the preparation, blending and integration of on-premise and external data sources to support descriptive through prescriptive analytics use cases.
Advanced Analytics
Forecast, identify trends, predict, and answer challenging business questions using predictive and prescriptive models.
Predictive Modeling Deployment
Help teams deploy predictive models into business processes with or without the use of coding in R and Python.
Event Triggering
Use predictive and prescriptive models to automatically trigger shipments, materials, sales, and more.
Analytic Apps
Turn analytic processes into applications can run using their own datasets and inputs.